223 citations · 349 across the 16 of their papers we have counts for
3 papers · 1 filter
When More Data Hurts: Optimizing Data Coverage While Mitigating Diversity Induced Underfitting in an Ultra-Fast Machine-Learned Potential
Jason B. Gibson, Tesia D. Janicki, Ajinkya C. Hire +3
Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parameterize the ML…
Superconductivity in pressurized ReMoB
S. Sinha, J. Lim, Z. Li +10
The recent surprising discovery of superconductivity with critical temperature = 32 K in MoB above 70 GPa has led to the search for related materials that may superconduc…
Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function
Jason B. Gibson, Ajinkya C. Hire, Philip M. Dee +4
Integrating deep learning with the search for new electron-phonon superconductors represents a burgeoning field of research, where the primary challenge lies in the computational i…